from bokeh.palettes import Spectral5
from bokeh.sampledata.autompg import autompg as df
from bokeh.transform import factor_cmap
from bokeh.sampledata.autompg import autompg_clean as df
from bokeh.plotting import figure


def mpg():
    '''bokeh绘制柱状图 自我实践案例2'''
    df.cyl = df.cyl.astype(str)
    group = df.groupby(['cyl', 'mfr'])
    index_cmap = factor_cmap('cyl_mfr', palette=Spectral5, factors=sorted(df.cyl.unique()), end=1)
    
    p = figure(plot_width=1000, plot_height=800, title="Mean MPG by # Cylinders and Manufacturer",
           x_range=group, tooltips=[("MPG", "@mpg_mean"), ("Cyl, Mfr", "@cyl_mfr")])
    
    p.vbar(x='cyl_mfr', top='mpg_mean', width=1, source=group,
       line_color="white", fill_color=index_cmap, )
    
    p.y_range.start = 0
    p.x_range.range_padding = 0.05  
    p.xgrid.grid_line_color = None
    p.xaxis.axis_label = "Manufacturer grouped by # Cylinders"
    p.xaxis.major_label_orientation = 1.2
    p.outline_line_color = None
    
    return p

def vbar_demo():
    '''bokeh绘制柱状图 案例1'''
    fig = figure(plot_width=300, plot_height=300)
    fig.vbar(
        x=[1, 2, 3, 4],
        width=0.5,
        bottom=0,
        top=[1.7, 2.2, 4.6, 3.9],
        color='navy'
    )
    
    return fig
